Motion tracking problems in Internet of Things (IoT) and wireless networking

"The dissertation focuses on inferring various motion patterns of internet-of-things (IoT) devices, by leveraging inertial sensors embedded in these objects, as well as wireless signals emitted (or reflected) from them. For instance, we use a combination of GPS signals and inertial sensors on drones to precisely track its 3D orientation over time, ultimately improving safety against failures and crashes. In another application in sports analytics, we embed sensors and radios inside baseballs and cricket balls and compute their 3D trajectory and spin patterns, even when they move at extremely high speeds. In a third application for wireless networks, we explore the possibility of physically moving wireless infrastructure like Access Points and basestations on robots and drones for enhancing the network performance. While these are diverse applications in drones, sports analytics, and wireless networks, the common theme underlying the research is in the development of the core motion-related building blocks. Specifically, we emphasize the philosophy of ""fusion of multi modal sensor data with application specific model” as the design principle for building the next generation of diverse IoT applications. To this end, we draw on theoretical techniques in wireless communication, signal processing, and statistics, but translate them to completely functional systems on real-world platforms."

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2018

Author dc:creator

• Gowda, Mahanth Krishnappa

Contributors dc:contributor

• Choudhury, Romit Roy
• Maggs, Bruce
• Vaidya, Nitin
• Nahrstedt, Klara
• Abdelzaher, Tarek

• Differential Global Positioning System (GPS)
• Carrier phases
• Unmanned aerial vehicle (UAV)
• Drones
• Inertial measurement units (IMU)
• Wireless
• Robotic networks
• Infrastructure
• Measurement
• Wearables
• Analytics
• Ultra-wideband (UWB)
• Sports
• Internet of Things (IoT)
• Embedded sensing

Statement dc:rights

• Copyright 2017 Mahanth Krishnappa Gowda

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/99369

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/99369